Dual-color Colocalization in Single-molecule Localization Microscopy to Determine the Oligomeric State of Proteins in the Plasma Membrane

Determining the oligomeric state of membrane proteins is critical for understanding their function. However, traditional ex situ methods like clear native gel electrophoresis can disrupt protein subunit interactions during sample preparation. In situ methods such as stepwise photobleaching have limitations due to high expression levels and limitations of optical resolution in microscopy. Super-resolution microscopy techniques such as single-molecule localization microscopy (SMLM) have the potential to overcome these limitations, but the stochastic nature of signals can lead to miscounting due to over-expression, background noise, and temporal separation of signals. Additionally, this technique has limited application due to the limited selection of fluorescent labels and the demanding control of laser power. To address these issues, we developed a dual color colocalization (DCC) strategy that offers higher tolerance to background noise and simplifies data acquisition and processing for high-throughput and reliable counting. The DCC strategy was used to determine the oligomeric states of membrane proteins of the SLC17 and SLC26 family with SMLM, providing a robust and efficient method for studying protein interactions.


Background
The composition of the quaternary structure of a protein tells us how this protein is operating and is therefore critical for the understanding of the molecular mechanisms behind their function. The experimental determination of protein oligomeric states is nontrivial. Several methods or strategies have been developed in the past decades, such as native gel electrophoresis (Schägger and von Jagow, 1991), stepwise photobleaching (Ulbrich and Isacoff, 2007), and single-molecule localization microscopy (SMLM) (Sengupta et al., 2011;Lee et al., 2012). Ex situ methods, such as native gel electrophoresis, rely on the extraction and purification of proteins for further investigation (Schägger and von Jagow, 1991). The detergents and mechanical forces exerted on protein complexes during these steps can, however, result in a loss of weaker interactions between subunits, creating a bias in the observed results. In response to these limitations, in situ methods, primarily centered on fluorescence microscopy, have been increasingly used in the past years. Often, this is in the form of stepwise photobleaching, where protein subunits are labeled with fluorophores and subsequently bleached by strong excitation (Ulbrich and Isacoff, 2007). This results in a stepwise loss of fluorescence for every bleached fluorophore. Due to the spatial limitations of light microscopy, however, this method only works if the density of expressed proteins is low. This mostly limits the application of this method to the use of Xenopus laevis oocytes, which are not a faithful representation of the cytosolic environment in mammalian cells. As a rather elegant strategy to implement super resolution microscopy technique, SMLM temporally separates the emissions from individual molecules to avoid overlapping signals from multiple emitters in the same diffraction limited spot. Fitting of these isolated signals can increase the resolution by up to tenfold. To achieve homogeneous labeling, the fluorophores are usually genetically encoded photoactivatable fluorescent proteins fused to the protein of interest. Thus, this type of SMLM is also called photoactivated localization microscopy (Betzig et al., 2006). Despite the achievable resolution and genetic labeling, it is still not possible to count the number of proteins within a sample by the number of fluorescent signals observed. For various reasons, not all fluorescent proteins will generate a signal during experiments (i.e., the recall rate is lower than 1). The distribution of the number of counts per protein complex is described by a binomial distribution, defined by the recall rate (Nan et al., 2013;Durisic et al., 2014). This strategy faces numerous challenges, primarily in that it demands a high recall rate (at least 0.5) of the fluorescent proteins. There are only a few options of suitable fluorescent proteins reported previously [e.g., PAmCherry (Durisic et al., 2014) and mEos3.2 (Zhang et al., 2012)]. Emission events from each fluorescent protein can extend over several frames and may be discontinuous. It is therefore imperative to develop algorithms that assign emission events to individual proteins within the complex. Furthermore, the binomial distributions of signals are often spuriously affected by a significant amount of background signals that are almost indistinguishable from true signals. We recently published a novel strategy, dual color colocalization (DCC) (Tan et al., 2022), circumventing these problems, as illustrated in the Graphical overview. The DCC strategy uses two covalently linked fluorescent proteins, serving as the marker (M) and the indicator (F), fused to the protein of interest. The marker is used to select the fraction of protein complexes that will be used for counting, while the indicator will be used to determine the oligomeric state (n) of the protein complex. This is done by experimental determination of the detection probability (R) of the protein complex, as given by the colocalization of the two fluorescent proteins: NMF is the number of protein complexes detected via both M and F, i.e., the colocalized protein complexes. NM is the overall number of clusters that show fluorescence of M, regardless of whether they are colocalized with F or not, and p is the recall rate of the indicator F. In this way, we disregard the complicated temporal separation (except to improve resolution based on SMLM) and assignment of emission events to individual proteins. This simplifies the imaging procedure and the data processing and builds a direct connection between the detection probability of the protein complex and its oligomeric state (Equation 1). Since our method relies on a cumulative probability instead of the probability densities of multiple detected states in a binomial distribution, the DCC strategy does not demand a high recall rate, thereby broadening the spectrum of usable fluorophores. For the marker protein, we choose the bright mVenus, given that the corresponding filter setting leads to a very low noise level, which is essential for the faithfulness of the result. Overall, this dual-color strategy greatly increases the signal-to-noise ratio in comparison with the single-color counting strategy. As we considered that the two adjacently linked fluorescent proteins may interfere with one another, or be truncated simultaneously, we elaborated our model by introducing another parameter, the coefficient of modification denoted by m, resulting in the following formula: In this protocol, we present the best practices that we established during the development of our method. We used DCC to determine the in situ oligomeric states of the vGlut family as monomers and SLC26 family as dimers. The DCC strategy has been proven to be an efficient improvement of the conventional strategy using SMLM to determine protein oligomeric state.

Materials and reagents
Equipment 1. Cell culture incubator with a constant temperature at 37 °C and 5% CO2 2. Laminar hood with an aspiration pump and a microscope for standard biosafety level 1 cell culture operations 3. Personal safety equipment for handling Piranha solution, including lab coat, acid-resistant gloves, and protective goggles 4. Glassware for preparing buffers and Piranha solution, including 100 mL and 1 L glass beakers, and 10 and 20 mL transfer pipettes. 5. Hot plate with magnetic stirrer for preparing solutions 6. Chemical fume hood for preparing and using Piranha solution 7. Total internal reflection fluorescence (TIRF) microscope capable of recording SMLM images in at least two separate color channels (plus activation 405 nm laser if photoactivatable proteins such as PAmCherry are used). Please consult with your local experts, if necessary, to determine the suitability of any available microscope. As a guide, the microscope we used in our original publication (Tan et al., 2022)

Preparation of plasmids
Clone the cDNA of the proteins of interest (POI) and the standards into the vector plasmid pcDNA3 or pcDNA5/FRT/TO. The proteins must be labeled with two fluorophores-in our case, mVenus and PAmCherry. We chose to fuse the coding sequence of mVenus and PAmCherry to the C-terminus of the coding region of the POI or the protein standard to simplify the procedure and because we had prior knowledge that the function of the proteins would remain largely intact. C-terminal linkage of the fluorophores, however, is not a requirement of our method. Fluorophores may be linked to the N-terminus or embedded within the protein itself. It may be necessary to perform functional experiments to assess whether the function is impaired by linkage to fluorescent proteins such as mVenus and PAmCherry. If possible, it may be possible to link one fluorophore to the N-terminus and the other fluorophore to the Cterminus of the protein. This would eliminate the need to consider unwanted truncation of the fluorophores and thus the need for the parameter m (Equation 2). We used barttin as the monomeric, the ClC-K and ClC-2 as the dimeric, EAAT2 as the trimeric, and Kcnj2 as the tetrameric standards. However, other plasma membrane proteins can also be tested and used as the standard. Some important criteria for choosing the standard proteins include: (1) the protein should be predominantly in the plasma membrane; (2) the protein should be expressed well in the chosen model cell line; and (3) the protein should have a mostly homogeneous oligomeric state, but not aggregate with others into super complexes or dissociate into individual subunits. We used a linker between the POI or standard protein and the fluorescent protein tag consisting of a flexible hydrophilic sequence with 10-30 amino acid residues. The linker should not be too long since it may increase the chance of protein cleavage. For more details about the standard proteins and the linker sequences, please refer to Tan et al. (2022). the beaker to hold the stirring bar, so it will not fall out. i. Cover the Coplin jar with the lid but do not seal it since gas will be generated in the cleaning process.
Note: Sealing the lid can lead to an explosion. j. Leave the filled jar under the laminar hood for five days.

B. Imaging of the standard proteins and the proteins of interest
Note: The following steps are specific to each individual microscope/control software combination. We give example values and settings for the microscope used in Tang et al. (2015) and Tan et al. (2022). The proper values for your setup (in particular for the camera and laser) will have to be locally determined and adjusted. Please discuss with your appropriate local experts and technicians, if necessary. 1. After fixation, take the coverslip with cells from the Petri dish and mount in a recording chamber. Our chamber was custom-made, holding up to 2 mL of solution and being placed on the stage of the microscope, stabilized with magnets.

4.
For the same purpose, add 2 mL of PBS for use as imaging buffer to a 1.5 mL microcentrifuge tube and let it warm up to the lab temperature. 5. During the bead incubation period, switch on the imaging system to warm it up for at least half an hour. 6. Align the lasers and adjust the laser intensities at the sample plane according to the manufacturer's instructions. Laser intensities must be chosen so that individual blinking events are spatially separated to allow for the extraction of super-resolution information. On the other hand, recording durations should allow for the activation and bleaching of all fluorescent proteins present in the sample. As a guide, for our experiments, we measured an intensity of 4.4 mW for the 514 nm laser and 5.4 mW for the 561 nm laser in the sample plane. We increased the intensity of the 405 nm laser during PAmCherry imaging slowly from 3.0 µW to 4.8 mW, so that each frame contained several spatially separated blinking events. 7. Aspirate the bead solution from the coverslip and rinse it gently with 1 mL of PBS pre-warmed to the lab temperature. 8. Remove the solution and gently add 1 mL of PBS pre-warmed to the lab temperature. 9. Put the imaging chamber onto the microscope stage. Let it stabilize for 15 min. To lower the background signal level and therefore increase the signal-to-noise ratio, either darken the lab or, even better, cover the stage area. 10. Set up the parameters for the camera to have 50 ms exposure and 85.59 ms as the duration between frames, including read-out of data from the camera. The frame duration affects the number of frames that a blinking event covers. Therefore, one must tweak the minimal number of localizations parameter for the clustering analysis if different values are chosen. 11. In widefield mode, use the green imaging channel (for mVenus) to choose a cell with moderate-to-low  12. Move the cell to the center of the view. Around the cell there should be 3-6 beads seen as bright spots in both color channels. Trajectories of the individual beads during the acquisition will be used for the sample drift correction. 13. In widefield mode, turn on the 561 nm laser for approximately 3,000 frames to bleach impurities within the sample. Background signals will be significantly reduced while PAmCherry molecules are largely unaffected without activation by the 405 nm laser. 14. Adjust the axial position of the sample stage to bring the beads into focus, as determined by reaching the maximal fluorescence from the beads. 15. With the white light and the 561 nm laser on, take a transmission image to record the location and shape of the cell and beads. 16. Switch to TIRF mode and record 4,000 frames with the 514 nm laser for mVenus. Usually, all mVenus molecules should be bleached at the end of recording. In case there are still many blinking events at the end, recording can be continued for another 2,000 frames. If this extended period still does not exhaust blinking events, it indicates either that the expression level is too high, or the laser power is too low. With the emission filter settings and the cleaning procedure, there should be very few blinking events on the green channel from the impurities outside of the cell. This is critical for the DCC algorithm to work. 17. With the same TIRF settings, record 6,000-12,000 frames with the 561 nm laser for PAmCherry, with 405 nm activation laser intensity increasing from the minimal to the maximal laser power (Section B.4), allowing the emission events to be sparsely distributed (as shown in Figure 1B) and all PAmCherry molecules to be bleached at the end of the recording. If 12,000 frames cannot exhaust all the blinking events within the cell, it may indicate that the expression level is too high. 18. Adjust the axial position of the sample stage and bring it to focus judging from the intensity of the beads.
If the offset is larger than 100 nm, then the recording is considered invalid due to large z-axis drift and must be discarded. 19. To record beads for the lateral chromatic aberration (LCA) correction using the fitted LCA protocol with the same sample, choose a region on the coverslip that does not contain any transfected cells but only beads (> 10, the more the better as long as they do not overlap with one another). In widefield mode, record 50 frames for each of the green and red channels as a single recording. Slightly move the sample to change the position of the beads and record another 50 frames. Repeat this moving and recording procedure numerous times to extract information from beads in at least 100 different positions, evenly distributed across the whole field of view.

C. Preparation of a bead sample
To record beads for the lateral chromatic aberration correction using the regional LCA protocol, prepare a beadonly sample for the SMLM recording. This sample can be stored in the dark at room temperature and lasts for several experiments. 1. Clean a microscope slide (75 mm × 25 mm) as for the coverslips with Piranha solution and let it air dry before use. 2. Thoroughly vortex the multi-color TetraSpeck fluorescent bead solution for 1 min. 3. Add 5 μL of bead solution into 400 μL of double-distilled water in a 1.5 mL Eppendorf tube and then vortex to mix it. 4. Add the diluted bead solution to a cleaned coverslip (25 mm) and let it air dry at room temperature. 5. After drying, place the coverslip on a microscope slide with the side of beads facing down towards the slide. 6. Dip a micropipette tip in nail polish and place 4-5 tiny drops on the edge of the coverslip to glue the coverslip onto the slide. 7. Once the nail polish is dry, the bead sample is ready for use. 8. Store the sample in the dark at room temperature until next imaging.

D. Imaging of the bead sample
Note: The following steps are specific to each individual microscope/control software combination. The exact values (in particular for the camera and laser) will have to be locally determined and adjusted for your setup. Please discuss with your appropriate local experts and technicians. 1. Launch the microscope and align the lasers as for the cell sample. 2. Mount the bead sample slide on a custom-made chamber that can stick to the microscope stage with magnets. The coverslip should be facing towards the objective when the slide is on the microscope stage. 3. Place the sample on the microscope stage and let it stabilize for approximately 20 min. 4. Set up the acquisition parameters so that pixel size, exposure time, and frame rates are the same as those for cell sample imaging. The excitation laser intensities can be reduced to avoid over-exposure since beads are much brighter than fluorescent proteins. 5. In widefield mode, record the bead sample for 50 frames each in the green and red channels as a single recording. 6. Slightly move the sample and repeat the imaging if the density of the beads is too low. Usually, a total of 500 beads or 500 positions from fewer beads in the field of view can be sufficient, as shown in Figure 2.

E. Extraction of localizations
1. Using SNSMIL software: We used SNSMIL (Tang et al., 2015) to localize the emission events in the recorded videos (image frames). This software was developed using recordings taken with our microscope setup and is therefore particularly optimized for our use case. 2. Alternatively, we have used the newer software SMAP (Ries, 2020) to extract localizations from the fluorescence signals in the recorded videos. This software uses improved algorithms and may work better with other microscopes. In our hands, we did not find a general advantage of using either SMAP or SNSMIL.

Data analysis
The DCC-SMLM algorithms have been integrated into a Python library. To use this library and the example of the analysis as explained below, a working knowledge of the Python programming language is required. For the examples given below, you also need to have some familiarity with Jupyter Notebooks. The protocol below should be studied while simultaneously working with the indicated files as stated in the beginning of each step. We have added a flowchart that may serve as a guide to the necessary steps and files used during analysis (Figure 3). For this, at least 500 beads spread across the whole field of view should be used. It is not required to record 500 separate beads, but the same sample may be moved in between recordings, resulting in multiple recordings that can be stacked together to increase the number of recorded positions. The CA parameters are saved in a .csv file and will be used by the scripts in the other steps (purple arrow). (B) Colocalization ratios of proteins with known oligomeric state must be individually determined. In our experience, at least 12 recordings per protein should be taken. The ratios are then used to calibrate the values of p and m in the DCC-SMLM model (Equation 2). These values will be used in the next step (brown arrow). (C) Colocalization ratios of proteins with unknown oligomeric states are recorded and